IBM, the number one Big Data vendor by revenue, enjoys talking with CIOs, and Eric Sall, the vice president of product marketing for the vendor’s Information Management business, is no different in that regard. Earlier this week on theCUBE, Sall popped in for a quick chat to discuss the Big Data use cases his company encounters most frequently with Wikibon’s Dave Vellante and Jeff Kelly.

Sall kicks off by describing what client organizations tend to get wrong from the start: they’re focused on the technology rather than what they can achieve with it. He explains that Big Data is different from traditional solutions, in the sense that the implementation is more interactive and iterative in nature; he adds that both the data and the process are unstructured.

Sall goes on to list the three issues that IBM clients are addressing with Big Data analytics: quality of service and targeting, operations, and risk. He then names the five most common use cases that Big Blue helped realize over the years:

Big Data Exploration

Organizations have huge amounts of highly variable data on their hands, including information generated behind the corporate firewall and social media interactions that live in the cloud. All this data has to explored and sorted before it can be applied to business problems, which is where IBM comes in. Sall says that one aircraft manufacturer is leveraging IBM’s InfoSphere Data Explorer platform to power a ‘maintenance war-room,’ where data from field is aggregated and processed. This project saves the company about $36 million annually.

Getting a 360 degree view of the customer

Sall next describes how enterprises are leveraging a combination of master data management, exploration, and integration solutions to construct customer profiles that enable them to tailor offerings for individual accounts. A medical device manufacturer used this technology to implement a ‘one more question’ system in its call center: its service reps ask customers for specific information at the end of each call to maximize the value of these interactions.

Security

Sall says that more and more organizations are applying Big Data analytics to perimeter security, IT security and fraud prevention. Video footage is processed to identify suspicious activity, and machine logs are scanned to detect analogies that may indicate the presence of an intruder.

Operations analytics

Companies and municipalities are tapping into smart devices and other data sources to catch problems early and serve large populations more effectively. Sall explains that streaming analytics solutions are utilized to collect, process and act upon data in real time; and to map individuals’ behavior in order to optimize city layouts.

Data warehouse augmentation

The final use study that Sall describes is data warehousing. Organizations are leveraging Big Blue’s technology to create ‘landing zones,’ wherein data is filtered before it enters the warehouse. The same technology is used to store archived data in a cost-efficient fashion without rendering it inaccessible.

For the full interview, check out the video below.